Paper Info
Title
Detection of Progression of Lesions in MRI Using Change Detection.
Abstract
Change detection is a process of identifying the changes in a state of an object over time. We use the phenomena of change detection to detect the changes occurring in MRI of brain having cancerous and non cancerous lesions. A Hybrid Particle Swarm Optimization algorithm that incorporates a Wavelet theory based mutation operation is used for segmentation of lesions in Magnetic Resonance Images. The segmented lesions are the Region of Interest. This method of using change detection algorithm would be helpful in detecting changes in Region of Interests of MRI with lesions and also to view the progress of treatment for cancerous lesions.
Year
DOI
Venue
2013
10.1007/978-3-319-02931-3_53
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON FRONTIERS OF INTELLIGENT COMPUTING: THEORY AND APPLICATIONS (FICTA) 2013
Keywords
Field
DocType
Region of Interest,Particle Swarm Optimization,Magnetic Resonance Imaging,Entropy,Multi-resolution Wavelet Analysis,Hybrid Particle Swarm Optimization,Wavelet Mutation
Particle swarm optimization,Change detection,Pattern recognition,Segmentation,Computer science,Artificial intelligence,Region of interest,Change detection algorithms,Magnetic resonance imaging,Wavelet
Conference
Volume
ISSN
Citations 
247
2194-5357
0
PageRank 
References 
Authors
0.34
6
3
Name
Order
Citations
PageRank
Ankita Mitra100.68
Arunava De2193.06
Anup Kumar Bhattacharjee3397.18